Since the advent of flying machines, engineers have strived to develop aircraft that can fly as flexibly as birds. From the original traditional control surface to the controllable morphing wing design, they all aim to improve the flight performance of drones, including the load capacity, maneuverability and stability. We believe that a single control method has certain limitations. For example, for roll control, the aileron rudder effect will be significantly reduced when flying at a high angle of attack (AOA), and the asymmetric deformation control of a wing is almost useless under the conditions of low-speed and small AOA. Until now, solutions to the above problems have remained largely unexplored. Therefore, the combination of wing deformation and ailerons is proposed to improve the roll control ability of drones. In this research, a new bionic deformable wing drone is designed, which demonstrates the advantages of the combination of ailerons and wing morphing in roll control and verifies that the symmetrical folding of a wing can change the flight envelope. The aerodynamic characteristics of the drone were tested in a numerical simulation, and its flight capabilities for different configurations were characterized in flight experiments.

Turbojet engines have a slow response and require mechanical assistance to perform vertical take-offs and landings. In this paper, we propose a vertical take-off and landing (VTOL) aircraft that contains one-dimensional thrust vectoring nozzle modules to solve the problem of dependence on the response of the turbojet. The turbojet engine is placed horizontally in the module, the rotational speeds are fixed, and the force along the turbojet axis remains constant as the nozzle rotates from the horizontal to the vertical position. The aircraft is composed of four modules, whose position and attitude control are realized by using the thrust difference caused by the different angles of the four vector nozzles. The modules no longer rely on the response speed of the turbojet engine, and controlling the angles of four nozzles makes it easier to operate the aircraft. The horizontal placement of the turbojet can reduce the thickness of the aircraft fuselage and decrease air resistance. The process of moving the nozzle from a horizontal to a vertical position prevents the engine from blowing directly on the ground and, thus, reduces the ground effect.

Morphing aircraft can alter their aerodynamic configuration to obtain multitask adaptability and improve flight performance. In this paper, we apply the variable sweep concept on a tandem-wing micro aerial vehicle (MAV) for multitask adaptability, the two canards of which can undergo backward sweep and the two wings can undergo forward sweep. The variable sweep morphing mode can not only weaken the additional inertia forces and moments caused by morphing, but can also maintain the longitudinal dynamic balance without elevator changes, which generates trim drag. What is more, it was demonstrated that sweep morphing can exert a great effect on the aerodynamic characteristics during the transition process, which are functionalized with the sweep inputs. The effect of addition forces and moments during the transition process was analyzed by dynamic response, and the longitudinal stability of the MAV were evaluated based on a linear parameter varying (LPV) model. Due to the dramatic effects of sweep morphing on the longitudinal stability, a gain scheduled transition controller based on a convex hull algorithm is proposed to guarantee the transition stability and improve the robustness, and a linear quadratic regulator (LQR) is used to guarantee the stability of the boundary point with the consideration of input saturation. Finally, the superior performance of the proposed controller was demonstrated by a theoretical simulation based on a nonlinear model.

In the wild, gliding birds dodge obstacles or predators by folding and twisting their wings swiftly to perform a rapid roll. Accordingly, the authors strive to explore the feasibility of improving the roll rate of drones through this bird‐inspired morphing method, by using the asymmetric sweepback of wings to simulate the contraction of birds’ wings and the deflection of the aileron to imitate wing torsion. Moreover, the effects of wing morphing on the centroid, inertia matrix, and aerodynamic characteristics of the drone are explored herein, and a nonlinear dynamic model is established. Furthermore, a novel cooperative strategy that combines wing morphing with aileron deflection for roll control is introduced, and a flight controller based on this cooperative strategy is developed. Finally, the superiority of the cooperative strategy and the accuracy of the dynamic modeling have been validated in the outdoor flights of the morphing wing drone.

In nature, gliding birds frequently execute intricate flight maneuvers such as aerial somersaults, perched landings, and swift descents, enabling them to navigate obstacles or hunt prey. It is evident that birds rely on different wing–tail configurations to accomplish a wide range of aerial maneuvers. For traditional fixed‐wing unmanned aerial vehicles (UAVs), pitch control primarily comes from the tail's elevators, while adjusting flight lift and drag involves deploying wing flaps. Although these designs ensure reliable flight, they compromise the drones’ maneuverability to maintain longitudinal stability. Therefore, the study introduces a biomimetic morphing wing UAV, and presents a pitch control strategy that simultaneously engages morphing wings, ailerons, and tail elevators. The pull‐up maneuver tests indicate that the proposed control method results in a pitch rate that is approximately 2.5 times greater than when using only the elevator control. A closed‐loop control system for the drone is also established. The closed‐loop flight experiment, which tracks a 45° pitch angle, demonstrates the effectiveness of the proposed coupled control method in adjusting the flight attitude. In addition, during cruising, the UAV employs three configurations, straight wing, forward‐swept wing, and back‐swept wing, to cater to different mission objectives and augment its flight capabilities.

This article proposes a deep extended dynamic mode decomposition structure based on the deep Koopman operators, residual and multihead attention modules (RS-DEDMD). The RS-DEDMD structure is designed for manipulator systems, using a 13-D Koopman operator to build the high-precision approximate linear model of the manipulator. Experiments show that the Koopman operator trained by RS-DEDMD have lower dimensions, higher prediction accuracy, fewer training iterations and faster convergence than other structures. A model predictive control system based on RS-DEMD (RSF-MPC) is constructed to verify the feasibility of using linearized model-based control. Experiments and simulations show the RSF-MPC is stable and outperforms other control methods in prediction and control capabilities. This demonstrates the accuracy of the linear model constructed by RS-DEDMD.